| import json | |
| import pandas as pd | |
| from datasets import Dataset, DatasetDict | |
| # Load the JSON data | |
| with open('tech_quotes.json', 'r') as f: | |
| data = json.load(f) | |
| # Convert JSON data to a DataFrame | |
| df = pd.DataFrame(data) | |
| # Create a Hugging Face dataset | |
| dataset = Dataset.from_pandas(df) | |
| # Optionally, split the dataset into train and test sets | |
| train_test_split = dataset.train_test_split(test_size=0.2) | |
| dataset_dict = DatasetDict({ | |
| 'train': train_test_split['train'], | |
| 'test': train_test_split['test'] | |
| }) | |
| # Save the dataset locally | |
| dataset_dict.save_to_disk('tech_quotes_dataset') | |
| # Optionally, push the dataset to the Hugging Face Hub | |
| dataset_dict.push_to_hub('your-username/tech-quotes-dataset') | |